How to Use the Mailsoftly MCP in Google ADK

Q: Can Google ADK restrict which Mailsoftly tools my agent uses?

Yes. You can use the optional toolnames filter when setting up the toolset. This lets you expose getcampaignclickdata for analysis while blocking write access entirely.

Q: How does Mailsoftly handle high-volume contact imports via Google ADK?

The agent loops through createbasecontact for individual inserts. If you hit API rate limits, you will need to implement backoff handling in your Python script, as the REST API enforces standard limits.

Q: Can Gemini analyze my campaign click data natively?

It handles it easily. The agent pulls raw stats via getcampaignclickdata and uses Gemini's massive context window to correlate link clicks with your broader marketing metrics.

Connect the Mailsoftly MCP Server to Google ADK. Feed campaign metrics straight into Gemini's massive context window.

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Connect Mailsoftly MCP to Google ADK

Create your Vinkius account to connect Mailsoftly to Google ADK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Mailsoftly with Google ADK

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Perplexity

Process massive campaign histories with Google ADK

Gemini models eat data for breakfast. When you connect the Mailsoftly MCP Server, your agent can pull years of email performance. It uses `list_sent_history` and `get_campaign_details` to dump thousands of rows of metadata straight into the 1M+ token context window. You do not need complex RAG pipelines to figure out why your open rates dropped. The agent looks at the entire dataset at once, spots the anomalies, and tells you exactly which subject lines tanked.

Bridge BigQuery segments to active contact lists

Enterprise teams already have their customer data sitting in BigQuery. Now your Gemini agent can bridge that warehouse directly to your email operations. The agent queries your BigQuery tables for high-value users, then loops through `create_base_contact` to push them into the CRM. After creating the contacts, it uses `add_contact_to_list` to build hyper-targeted segments. You skip the CSV exports entirely. The agent handles the ETL work and preps the audience for your next send.

Trigger data-driven campaign deployments

Your agents can actually execute the marketing playbooks they write. Once the audience is segmented, the agent verifies the campaign setup via `list_marketing_campaigns`. If everything looks correct, it fires the `send_campaign_to_all` tool. The integration works flawlessly on Google Cloud infrastructure through the MCP protocol. You can restrict the exposed tools using the tool_names filter in the ADK, ensuring your analytical agents only read data while your deployment agents handle the actual sending.

Setup guide

Set up Mailsoftly MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Mailsoftly tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Mailsoftly_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Mailsoftly tools via MCP.",
    tools=mcp_tools,
)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Mailsoftly. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Mailsoftly MCP in Google ADK

Install google-adk and configure a McpToolset using StreamableHttpServerParameters. Point the URL to your Vinkius MCP server endpoint and pass the toolset to your LlmAgent.

Yes. You can use the optional tool_names filter when setting up the toolset. This lets you expose `get_campaign_click_data` for analysis while blocking write access entirely.

The agent loops through `create_base_contact` for individual inserts. If you hit API rate limits, you will need to implement backoff handling in your Python script, as the REST API enforces standard limits.

It handles it easily. The agent pulls raw stats via `get_campaign_click_data` and uses Gemini's massive context window to correlate link clicks with your broader marketing metrics.

Vinkius operates on a zero-trust architecture. When your agent queries subscriber collections or campaign details, the connection is authenticated via a single endpoint token and runs in an ephemeral container. We never store your BigQuery exports or email data.

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